Scaling up health interventions in resource-poor countries: what role does research in stated-preference framework play?

Abstract

Despite improved supply of health care services in low-income countries in the recent past, their uptake continues to be lower than anticipated. This has made it difficult to scale-up those interventions which are not only cost-effective from supply perspectives but that might have substantial impacts on improving the health status of these countries. Understanding demand-side barriers is therefore critically important. With the help of a case study from Nepal, this commentary argues that more research on demand-side barriers needs to be carried out and that the stated-preference (SP) approach to such research might be helpful. Since SP techniques place service users' preferences at the centre of the analysis, and because preferences reflect individual or social welfare, SP techniques are likely to be helpful in devising policies to increase social welfare (e.g. improved service coverage). Moreover, the SP data are collected in a controlled environment which allows straightforward identification of effects (e.g. that of process attributes of care) and large quantities of relevant data can be collected at moderate cost. In addition to providing insights into current preferences, SP data also provide insights into how preferences are likely to respond to a proposed change in resource allocation (e.g. changing service delivery strategy). Finally, the SP-based techniques have been used widely in resource-rich countries and their experience can be valuable in conducting scaling-up research in low-income countries.

Figure 1

Simulated impact of location on probability of using prenatal care and trained delivery assistance in Nepal. Purple bar – Prenatal care. Red bar – Trained delivery assistance. This graph is based on the data provided in [36].